1. Field of the Invention
The present invention generally relates to a handwritten character recognition device, and more particularly to an on-line handwritten character recognition device that recognizes handwritten characters inputted in an on-line manner.
2. Description of the Prior Art
FIG. 1 is a block diagram showing an overview operation of an on-line handwritten character recognition device. In an operation, a character is inputted to the device by means of an input device, such as a tablet, in step S100. Preprocessing such as noise elimination is carried out for the input character data in order to facilitate extraction of an input pattern in step S101. Basic patterns forming the input character are extracted from the input character after the preprocessing, and features of the input character are extracted from the respective basic patterns of the input character in step S102. After that, postprocessing is performed, if necessary. A structure analysis at a whole character level is carried out, and the input character is recognized in step S103. The recognized input character is outputted to an output device, such as a display or a printer in step S104.
As character recognition methods for the on-line handwritten character recognition device, a pattern matching method and a dynamic programming (hereinafter simply referred to as "DP") method are known.
[i] Pattern Matching Method
The pattern matching method is the principal method of pattern recognition, and directly compares two patterns (an input pattern and a reference pattern) with each other. More particularly, there are a minimum distance identification method, and a degree-of-similarity identification method.
FIGS. 2B and 2C respectively illustrate examples of an input pattern and a reference pattern used in the minimum distance identification method, which is one of the pattern matching methods.
A match-degree g.sup.(a,s) expressed in the following equation is obtained using the patterns shown in FIGS. 2B and 2C: ##EQU1## where Xai denotes pixel data of the input pattern, and Xsi denotes pixel data of the reference pattern. The input pattern is compared with a plurality of reference patterns, and one of the reference patterns having the smallest match-degree is identified.
[ii] DP Method
In the DP method, the input pattern is divided into a plurality of parts, and patterns contained in the respective parts are symbolized. Then, a reference pattern is obtained from a sequence of symbols, using an identification automaton theory.
The above-mentioned pattern matching method is greatly affected by deformation of the input pattern. Hence, preprocessing and postprocessing are required to correct the deformation of the input pattern. Further, the reference patterns stored in a dictionary for comparison consist of pixels, and hence it is necessary for the dictionary to have at least the following storage capacity (see FIG. 2A):
Storage capacity=(number Pl of pixels in the longitudinal direction).times.(number Pc of pixels in the lateral direction).times.(number of reference patterns). Hence, the large capacity is required for the dictionary.
The DP method is not affected by deformation of the input pattern. However, the DP method needs a long operation time.